Biology subjects

Bazin, P.-L.

Publications and source records attributed to Bazin, P.-L..

At least 19 recordsLinked to original sources

bioRxiv2026

Selective nigrosome vulnerability in Parkinson's disease revealed by histology-anchored ultra-high-field quantitative MRI

Selective vulnerability is a hallmark of Parkinson's disease (PD): post-mortem, dopamine-containing cell loss in the substantia nigra first and most severely affects calbindin-poor compartments termed nigrosomes. Testing this in vivo has been limited by circularity, as MRI studies have delineated nigrosomes from the same disease-related contrast they then measure. Here, we warp histology-derived, calbindin-validated probabilistic masks of nigrosomes 1-5 into a cohort-specific multimodal 7 Tesla quantitative MRI template, providing a degeneration-independent anatomical scaffold, in 28 patients with PD and 28 age- and sex-matched controls. In controls, nigrosomes differ from the surrounding nigral matrix in magnetic susceptibility and R1. PD shifts nigrosomal values upward relative to the matrix in susceptibility, R2*, and R1, concentrated in nigrosomes 1, 2, and 4, whereas whole-nigra analysis shows no group difference. Within the matrix, disease effects are largest caudally and emerge dorsally from the ventral tier, and susceptibility alterations in nigrosomes 1 and 4 track contralateral motor symptoms asymmetry. The multimodal pattern suggests that the detectable signal reflects predominantly secondary, iron-associated glial processes rather than neuronal loss itself. These findings recover the post-mortem spatial pattern of nigral vulnerability in vivo and establish a degeneration-independent framework for subregional nigral imaging in PD.

neuroscience↗

bioRxiv2026

Giving you five: A neuroimaging atlas of the nigrosomes in the substantia nigra based on 3D histology

Nigrosomes are formed by clusters of pigmented dopaminergic cells in the substantia nigra that critically contribute to dopaminergic function. The ever-increasing resolution of ultra-high-field MRI brings clinical imaging of these clusters into reach, promising unprecedented insight into the functional role of the nigrosomes and their early degeneration in Parkinsons disease. However, due to the nigrosomes small extents and intricate shapes, they are not included in current MRI brain atlases, preventing nigrosome-specific MRI data analysis. We provide a comprehensive 3D histological atlas of the five nigrosomes co-aligned to the widely-used MNI152 2009b space. This atlas is based on 3D-reconstructed, ultra-high-resolution block-face images and gold-standard nigrosome delineations in calbindin-D28K immunohistochemistry. We validated the atlass accuracy using the multimodal ultra-high-resolution post mortem BigBrain dataset and demonstrated its consistency with qualitative nigrosome atlases based on classical 2D histology. We provide detailed usage instructions for applying our atlas to ultra-high-resolution and -field MRI data. The openly available atlas enables neuroimaging studies of the nigrosomes, opening a new avenue toward understanding the differential involvement of the nigrosomes in the healthy and diseased brain and the development of neuroimaging biomarkers of dopaminergic neurodegeneration.

neuroscience↗

bioRxiv2025

Spatial layout of visual specialization is shaped by competing default mode and sensory networks

Understanding how the brain encodes information started with a map but turned into a maze: paths multiplied; boundaries blurred. Neurons tuned to specific features are not confined to single regions, but distributed across the cortex. Retinotopy, once thought limited to early visual areas, now appears in over 20 cortical regions--from the tip of the occipital cortex to the shore of the lateral frontal cortex. To describe and understand these complex mosaics of functional specialization, we focus on the spatial influences that shape their emergence across the cortical sheet. To this end, we developed Spatial Component Decomposition (SCD), a sparse dictionary learning framework that locates sources of spatial influence without relying on prior assumptions from systems neuroscience. Applied to MRI data capturing retinotopic maps, SCD reveals a dominant linear gradient extending over 60 mm from V1 and covering all the known posterior visual areas. Yet, it also revealed systematic competition from other primary sensory areas and default mode transmodal hubs. These suppressive influences shape the cortical embedding of visual information, even during purely visual tasks. Our results suggest that functional specialization emerges from spatial competition between representational systems--not just from feedforward inputs.

neuroscience↗

bioRxiv2025

Mesoscale imaging of the human cerebellum reveals converging regional specialization of its morphology, vasculature and cytoarchitecture.

The human cerebellar cortex contains the highest density and number of neurons in the human brain, yet this thin and tightly-folded structure has remained largely inaccessible to in-vivo imaging. We introduce an imaging framework to enable high-resolution, comprehensive imaging of the human cerebellar cortex. We validated the in-vivo estimates of cortical morphology against post-mortem measures. Crucially, our findings challenge the commonly held view of the cerebellar cortex as being uniform. Our findings reveal interlobular heterogeneity in both cortical morphology and vascular organization. We demonstrate that this spatial heterogeneity correlates with granular layer cell density. This convergence of morphology, cytoarchitecture and vascularization offers new mechanistic insights and reframes how cerebellar structure and function should be interpreted in health and disease.

neuroscience↗

bioRxiv2025

A unified imaging-histology framework for superficial white matter architecture studies in the human brain

The superficial white matter (SWM), immediately beneath the cortical mantle, is thought to play a major role in cortico-cortical connectivity as well as large-scale brain function. Yet, this compartment remains rarely studied due to its complex organization. Our objectives were to develop and disseminate a robust computational framework to study SWM organization based on 3D histology and high-field 7T MRI. Using data from the BigBrain and Ahead 3D histology initiatives, we first interrogated variations in cell staining intensities across different cortical regions and different SWM depths. These findings were then translated to in-vivo 7T quantitative myelin-sensitive MRI, including T1 relaxometry (T1 map) and magnetization transfer saturation (MTsat). As indicated by the statistical moments of the SWM intensity profiles, the first 2 mm below the cortico-subcortical boundary were characterized by high structural complexity. We quantified SWM microstructural variation using a non-linear dimensionality reduction method and examined the relationship of the resulting microstructural gradients with indices of cortical geometry, as well as structural and functional connectivity. Our results showed correlations between SWM microstructural gradients, as well as curvature and cortico-cortical functional connectivity. Our study provides novel insights into the organization of SWM in the human brain and underscores the potential of SWM mapping to advance fundamental and applied neuroscience research. HighlightsO_LIDeveloped an anatomy-based open science framework to study SWM organization based on 3D post-mortem histology and/or in-vivo high-field MRI C_LIO_LIThe first 2 mm into the white matter are characterized by high structural complexity C_LIO_LIInter-regional trends in SWM microstructural variation, which related to cortical geometry, as well as cortico-cortical connectivity C_LI

neuroscience↗

bioRxiv2025

The intrinsic cortical geometry of reading

How does the brain support the complex processes that allow us to read? Using predictive modeling we establish that visual and association cortex are closer together in individuals with stronger oral reading ability. These findings indicate that large-scale cortical geometry provides a scaffold that supports the coordinated processing required to read.

neuroscience↗

bioRxiv2024

Joint models reveal human subcortical underpinnings of choice and learning behaviour

Decision making and learning processes together enable adaptive goal-oriented behaviour. Animal studies demonstrated the importance of subcortical regions in these cognitive processes, but the human subcortical contributions remain poorly characterised. Here, we study choice and learning processes in the human subcor-tex, using a tailored ultra-high field 7 T fMRI imaging protocol combined with joint models. Joint models provide unbiased estimates of brain-behaviour rela-tions by simultaneously including behavioural and neural data at the participant and group level. Results demonstrate relations between subcortical regions and the adjustment of decision urgency. Value-related BOLD differences were found with opposite BOLD polarity in different parts of the striatum. Multiple sub-cortical regions showed BOLD signatures of reward prediction error processing, but contrary to expectations, these did not include the dopaminergic midbrain. Combined, this study characterises the human subcortical contributions to choice and learning, and demonstrates the feasibility and value of joint modelling in facilitating our understanding of brain-behaviour relationships.

neuroscience↗

bioRxiv2024

Multimodal laminar characterization of visual areas along the cortical hierarchy

Understanding the relationship between brain structure and function is a central goal in neuroscience. While post-mortem studies using microscopic techniques have provided detailed insights into the brains cytoarchitectonic and myeloarchitectonic patterns, linking these structural findings to functional outcomes remains challenging. Magnetic resonance imaging (MRI) has emerged as a powerful non-invasive tool for studying both structure and function, but discrepancies in spatial resolution between structural and functional imaging, especially in layer-fMRI, complicate the interpretation of functional results. In this study, we explore how visual cortical hierarchy relates to microscopic and mesoscopic laminar features. Focusing on visual areas that span progressive hierarchical levels, V1, V2, V3, and hMT+, we apply a multimodal approach combining post-mortem histology, post-mortem and in-vivo quantitative MRI (qMRI), and resting-state layer-fMRI. Using the open-access post-mortem AHEAD dataset, which integrates histological and qMRI contrasts from the same brain samples, we bridge microscopic observations with qMRI data. In parallel, we incorporate high-resolution [Formula] MRI and resting-state layer-fMRI from the same participant, allowing for a comparative analysis of laminar profiles across cortical depth. For computing laminar profiles, we developed an analysis pipeline that bridges histology images, mesoscopic qMRI, and layer-fMRI. Our findings highlight parvalbumin laminar profiles (reflecting interneuron parvalbumin density) as the most discriminative feature for differentiating brain areas. Additionally, we report laminar quantitative [Formula] profiles from post-mortem and in-vivo data, together with [Formula]-weighted resting-state layer-fMRI, all of which exhibit a similar overall shape across modalities. Using our methodological framework, a similar laminar characterization can be extended to study other brain regions. Generative models for layer fMRI will benefit from incorporating these new empirical microstructural (parvalbumin) and physical quantitative [Formula] data, leading to more area-specific and accurate models. HighlightsO_LIWe present a multimodal analysis of the laminar organization of four visual regions (V1, V2, V3, hMT+), characterizing progressive visual hierarchy levels in humans. This analysis spans from post-mortem microscopy and quantitative MRI (qMRI) to in-vivo qMRI and laminar fMRI during resting state. C_LIO_LIAmong the three microscopy contrasts, parvalbumin, a marker of interneuron density, emerges as the most distinctive regional feature. Notably, the parvalbumin laminar profiles vary across hierarchy levels, with hMT+ showing the greatest divergence compared to V1, V2, and V3. C_LIO_LIQuantitative [Formula] measurements, from both post-mortem and in-vivo data, reveal a clear increase towards the superficial cortical layers. These depth-dependent patterns closely mirror the laminar profiles observed in both task and resting-state fMRI. C_LIO_LISurprisingly, no substantial difference was observed in laminar [Formula] profiles between post-mortem and in-vivo data across the visual areas. C_LI

neuroscience↗

bioRxiv2024

Subcortical nuclei of the human ascending arousal system encode anticipated reward but do not predict subsequent memory

Subcortical nuclei of the ascending arousal system play an important role in regulating brain and cognition. However, functional MRI of these nuclei in humans involves unique challenges due to their size and location deep within the brain. Here, we used ultra-high-field MRI and other methodological advances to investigate the activity of six subcortical nuclei during reward anticipation and memory encoding: the locus coeruleus, basal forebrain, median and dorsal raphe nuclei, substantia nigra and ventral tegmental area. Participants performed a monetary incentive delay task, which successfully induced a state of reward anticipation, and a 24-hour delayed surprise memory test. Region-of-interest analyses revealed that activity in all subcortical nuclei increased in anticipation of potential rewards as opposed to neutral outcomes. In contrast, activity in none of the nuclei predicted memory performance 24 hours later. These findings provide new insights into the cognitive functions that are supported by the human ascending arousal system.

neuroscience↗

bioRxiv2024

Cortical contributions to attentional orienting and response cancellation in action stopping

Action cancellation involves the termination of planned or initiated movement. Contemporary models of action cancellation, such as the Pause-then-Cancel model, propose that this occurs via a two-stage process, initiated in the cortex by the pre-supplementary motor area (preSMA) and inferior frontal gyrus (IFG). Previous experimental work using electromyography (EMG) has identified that the cancellation of actions can involve the partial activation of the responding muscles, which does not result in an overt behavioural response. In this study, we used functional near-infrared spectroscropy (fNIRS) to investigate the neural correlates of these partial responses in a modified stopping task (a response- and stimulus-selective stop-signal task), controlling for the attentional effects that have long confounded action cancellation research by comparing responses to stop stimuli with those to ignore stimuli. We identified stopping-related activity in the preSMA but not the IFG, consistent with predictions of the Pause-then-Cancel model. Additionally, we observed increased preSMA activity in trials where no partial responses occurred, potentially due to the cumulative effect of different inhibitory processes in those trials. This study also highlights the utility of combining fNIRS and EMG in examining the cortical correlates and dynamic processes involved in action cancellation.

neuroscience↗

bioRxiv2024

The ageing stopping network: Regional and network changes in the IFG, preSMA, and STN across the adult lifespan

Response inhibition, the cancellation of planned movement, is essential for everyday motor control. Extensive fMRI and brain stimulation research provides evidence for the crucial role of a number of cortical and subcortical regions in response inhibition, including the subthalamic nucleus (STN), pre-supplementary motor area (preSMA), and the inferior frontal gyrus (IFG). Current models assume that these regions operate as a network, with action cancellation originating in the cortical areas and then executed rapidly via the subcortex. Response inhibition slows in older age, a change that has been attributed to deterioration or changes in the connectivity and integrity of this network. However, previous research has mainly used whole-brain approaches when investigating changes in structural connectivity across the lifespan, or have used simpler measures to investigate structural ageing. Here, we used high-resolution quantitative and diffusion MRI to extensively examine the anatomical changes that occur in this network across the lifespan. We found substantial changes in iron concentration in these tracts, increases in the apparent diffusion coefficient, and some evidence for demyelination. Conversely, we found very little evidence for age-related anatomical changes in the regions themselves. We propose that some of the functional changes observed in these regions in older adult populations (e.g., increased BOLD recruitment) are a reflection of alterations to the connectivity between the regions, rather than localised regional change.

neuroscience↗

bioRxiv2024

Tempo-dependent selective enhancement of neural responses at the beat frequency can be explained by both an oscillator and an evoked model

A crucial mechanism for the brain to make sense of the auditory environment is the synchronization of neural responses to external temporal regularities, such as a musical beat. It is debated whether this synchronization and the resulting beat percept reflect phase alignment of endogenous neural oscillations to the external regularity (entrainment), or evoked responses to the rhythmic stimulus (tracking). Here, we use the tempo-dependent properties of beat processing to differentiate between the two accounts. Participants listened to a repeating rhythmic pattern at different speeds. Behaviorally, they consistently tapped at the preferred beat rate (around 2 Hz) across tempi, shifting to higher metrical levels as tempo increased. We found a similar shift in EEG data, where the metrical level at which neural synchronization was strongest depended on tempo. This selective enhancement is consistent with entrainment accounts and could indeed be mimicked by an oscillator model. However, importantly, the results were also captured by a model simulating evoked responses. Together, our findings demonstrate that while neural responses to rhythm are selectively enhanced at the beat rate, this enhancement need not be taken as evidence for entrainment, but can also be explained by successive evoked responses.

neuroscience↗

bioRxiv2024

Exploring working memory updating processes of the human subcortex using 7T MRI

A growing body of research suggests that dopamine is involved in working memory updating and that the striatum takes up a critical role in the subprocess of working memory gating (Braver & Cohen, 2000; Cools & DEsposito, 2011; DArdenne et al., 2012; Jongkees, 2020). In this study, we investigated subcortical-in particular, possible dopaminergic-involvement in working memory updating subprocesses using the reference-back task and ultra-high field 7 Tesla fMRI. Using a scanning protocol optimized for BOLD-sensitivity in the subcortex, we found no evidence of subcortical activation during working memory gate opening, predominantly activations in frontoparietal network regions, which challenges the idea of a striatal gating mechanism. However, during gate closing, subcortical activation was observed. Furthermore, a ready-to-update mode demonstrated large-spread subcortical activation, including basal ganglia nuclei, suggesting that the basal ganglia are engaged in general updating processes rather than specifically controlling the working memory gate. Moreover, substituting new information into working memory elicited activation in dopamine-producing midbrain regions along with the striatum, thalamus, and prefrontal cortex, indicating engagement of the basal ganglia-thalamo-cortical loop possibly driven by (potential) dopaminergic activity. These findings expand our understanding of subcortical regions involved in working memory updating, shifting the focus from gate opening to substitution as a midbrain-driven updating process.

neuroscience↗

bioRxiv2024

A Comparative Machine Learning Study of Connectivity-Based Biomarkers of Schizophrenia

Functional connectivity holds promise as a biomarker of psychiatric disorders. Yet, its high dimensionality, combined with small sample sizes in clinical research, increases the risk of overfitting when the aim is prediction. Recently, low-dimensional representations of the connectome such as macroscale cortical gradients and gradient dispersion have been proposed, with studies noting consistent gradient and dispersion differences in psychiatric conditions. However, it is unknown which of these derived measures has the highest predictive capacity and how they compare to raw connectivity. Our study evaluates which connectome features -- functional connectivity, gradients, or gradient dispersion -- best identify schizophrenia. Figure 1 summarizes this work. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=41 SRC="FIGDIR/small/573898v1_fig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@12c0fdorg.highwire.dtl.DTLVardef@13c4702org.highwire.dtl.DTLVardef@59f8d7org.highwire.dtl.DTLVardef@e00f56_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Overview of the methods and main outcome of the paper. Schematic images: Flaticon.com. NC: neurotypical controls, SCZ: patients with schizophrenia. C_FIG Surprisingly, our findings indicate that functional connectivity outperforms its low-dimensional derivatives such as cortical gradients and gradient dispersion in identifying schizophrenia. Additionally, we demonstrated that the edges which contribute the most to classification performance are the ones connecting primary sensory regions.

neuroscience↗

bioRxiv2023

The canonical stopping network: Revisiting the role of the subcortex in response inhibition

This study investigates the functional network underlying response inhibition in the human brain, particularly the role of the basal ganglia in successful action cancellation. Functional magnetic resonance imaging (fMRI) approaches have frequently used the stop-signal task (SST) to examine this network. We merge five such datasets, using a novel aggregatory method allowing the unification of raw fMRI data across sites. This meta-analysis, along with other recent aggregatory fMRI studies, does not find evidence for the innervation of the hyperdirect or indirect cortico-basal-ganglia pathways in successful response inhibition. What we do find, is large subcortical activity profiles for failed stop trials. We discuss possible explanations for the mismatch of findings between the fMRI results presented here and results from other research modalities that have implicated nodes of the basal ganglia in successful inhibition. We also highlight the substantial effect smoothing can have on the conclusions drawn from task-specific GLMs. First and foremost, this study presents a proof of concept for meta-analytical methods that enable the merging of extensive, unprocessed or unreduced datasets. It demonstrates the significant potential that open-access data sharing can offer to the research community. With an increasing number of datasets being shared publicly, researchers will have the ability to conduct meta-analyses on more than just summary data.

neuroscience↗

bioRxiv2022

Assessing Quantitative MRI Techniques using Multimodal Comparisons

The study of brain structure and change in neuroscience is commonly conducted using macroscopic morphological measures of the brain such as regional volume or cortical thickness, providing little insight into the microstructure and physiology of the brain. In contrast, quantitative MRI allows the monitoring of microscopic brain change non-invasively in-vivo, and provides normative values for comparisons between tissues, regions, and individuals. To support the development and common use of qMRI for cognitive neuroscience, we analysed a set of qMRI metrics (R1, R2*, Magnetization Transfer saturation, Proton Density saturation, Fractional Anisotropy, Mean Diffusivity) in 101 healthy young adults. Here we provide a comprehensive descriptive analysis of these metrics and their linear relationships to each other in grey and white matter to develop a more complete understanding of the relationship to tissue microstructure. Furthermore, we provide evidence that combinations of metrics may uncover informative gradients across the brain by showing that lower variance components of PCA may be used to identify cortical gradients otherwise hidden within individual metrics. We discuss these results within the context of microstructural and physiological neuroscience research.

neuroscience↗

bioRxiv2021

Depth-resolved intersubject functional correlation of 7T BOLD signals reveals increased stimulus related information sharing across deep layers in premotor and parietal nodes for predictable actions

While the brain regions involved in action observation are relatively well documented in humans and primates, how these regions communicate to help understand and predict actions remains poorly understood. Traditional views emphasized a feed-forward architecture in which visual features are organized into increasingly complex representations that feed onto motor programs in parietal and then premotor cortices where the matching of observed actions upon the observers own motor programs contributes to action understanding. Predictive coding models place less emphasis on feed-forward connections and propose that feed-back connections from premotor regions back to parietal and visual neurons represent predictions about upcoming actions that can supersede visual inputs when actions become predictable, with visual input then merely representing prediction errors. Here we leverage the notion that feed-back connections target specific cortical layers to help adjudicate across these views. Specifically, we test whether observing sequences of hand actions in their natural order, which permits participants to predict upcoming actions, triggers more feed-back input to parietal regions than seeing the same actions in a scrambled sequence that hinders making predictions. Using submillimeter fMRI acquisition at 7T, we find that watching predictable sequences triggers more action-related activity (as measured using intersubject functional correlation) in the parietal cortical area PFt at depths receiving feed-back connections (layers III and V/VI) than watching the exact same actions in scrambled and hence unpredictable sequence. In addition, functional connectivity analysis performed using intersubject functional connectivity confirms that these increased action-related signals in PFt could originate from ventral premotor region BA44. This data showcases the utility of intersubject functional correlation in combination with 7T MRI to explore the architecture of social cognition under more naturalistic conditions, and provides evidence for models that emphasize the importance of feed-back connections in action prediction.

neuroscience↗

bioRxiv2021

Charting human subcortical maturation with in vivo 7 T MRI

The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.

neuroscience↗